Abstract: Wireless communication systems have been evolving since the first generation. With the fifth generation (5G) of wireless systems, the focus is not only on the evolutionary aspect of increased data rate, but also on novel performance metrics for emerging applications, such as autonomous driving, industrial automation, and Tactile Internet applications. In this context, the wireless system design has increasingly turned its focus on guaranteeing extremely high reliability and low latency. Hence, the developments of 5G systems require leveraging novel techniques to cope with the heterogeneity of applications and to achieve their stringent requirements.

This talk focuses on the definition of reliability in wireless systems and on fundamental techniques to achieve reliability requirements in 5G networks. Firstly, definitions and concepts of reliability theory, which provides a mathematical tool to evaluate and improve the reliability and availability of technical components and systems, are applied and extended to wireless networks. Then, the signal-to-interference-plus-noise ratio (SINR) is identified as a major metric to study the impact of the wireless link quality on high availability. For addressing new requirements imposed on emerging 5G applications, e.g. outage probabilities of 10-7 or less, a highly accurate modelling of the SINR is needed. A stochastic model of the SINR including the shadow fading, noise power, and best server policy is presented as an alternative to highly complex wireless system simulations providing extreme accuracy and a tool to evaluate the outage probability at any position in any given wireless network. As diversity techniques, such as multi-point connectivity which are also supported by the 5G systems, are widely accepted to be key to achieve high reliability, the proposed SINR model is extended to multi-point transmission. Numerical evaluations reveal the applicability of the model to multi-point connectivity. However, unlike the general understanding, it will be shown that ensuring low outage probabilities does not necessarily imply improved reliability in multi-user systems, in which resources are shared. In this regard, a novel matching theory-based algorithm aiming for guaranteeing reliability requirements in a multi-cellular, multi-user system will be presented. The proposed algorithm yields a maximum gain of 150% as compared to fixed multi-point approaches. The talk will be concluded with a research vision for how the results obtained so far can be extended to design highly flexible and autonomous tools for investigating future wireless systems, which simultaneously support multiple services with diverse requirements. These tools will open the new era for studying the feasibility of emerging applications under given conditions and the coexistence of various use cases with diverse and (partially) competing requirements, for developing novel concepts and end-to-end solutions for intelligent and predictive resource management in wireless systems, and for applying and implementing these concepts and solutions into real systems.

Biography: Meryem Simsek is a Principal Investigator at the International Computer Science Institute Berkeley and a senior Research Group Leader at the Technical University Dresden. She earned her Dipl.-Ing. degree in Electrical Engineering and Information Technology and her Ph.D. on "Learning-Based Techniques for Intercell-Interference Coordination in LTE-Advanced Heterogeneous Networks" from the University of Duisburg-Essen, Germany in 2008 and 2013, respectively. Her current research focuses on modelling and optimizing emerging wireless systems, heterogeneous wireless networks, achieving high reliability and low latency in 5G networks and Tactile Internet applications. Further research interests are based on developing novel tools for network management, wireless edge automation, and autonomous wireless networks and implementing these tools into real systems. She is the recipient of the fellowships by the German Physical Society (2004-2005) and the German National Academic Foundation, which is only granted to the outstanding 0.5% students in Germany (2004-2008). She holds the titles of the first electrical engineering student who has graduated before the regular duration of study and the best Diplom-graduate in Electrical Engineering at the University of Duisburg-Essen (2008). Meryem Simsek received the IEEE Communications Society Fred W. Ellersick Prize 2015 for IEEE Communications Magazine paper "When Cellular Meets WiFi in Wireless Small Cell Networks". In addition, she has initiated and is chairing the IEEE Tactile Internet Technical Committee and is serving as the secretary of the IEEE P1918.1 standardization working group, which she has co-initiated. She is also holding the position of the "industry and student activities coordinator" in the IEEE Women in Communications Engineering (WICE) committee.

Abstract: As we realize that many profoundly important problems, such as decoding cancerous genes, prime factorization for cryptography, accurate weather prediction, etc., cannot be solved efficiently even with the best of our digital computers, we need look for new computing paradigms beyond the ageing von Neumann architecture, Boltzmann tyranny, and the Turing limit.

Although chaos sounds antithetical to solving problems, many of the finest computers in nature, from neural circuits in the brain, to evolutionary natural selection, operate at the "edge of chaos" within a "locally active" region, to produce "complexity and emergence". Here I will illustrate how these purely mathematical constructs, firmly established less than a decade ago, can be utilized via electronics to construct efficient computing systems. Taking this rather different route also necessitates a completely revamped research into all the building blocks of a computing system, including discovering relevant nonlinear material properties, constructing radically new locally active device models, and designing a device + problem-centric system architecture. I will use an illustrative example, where we discovered a strange thermal property of a material during its Mott transition that exhibited local activity and controlled electronic chaos, an ensemble of which was used to build a transistorless analogue Hopfield neural network. This scalable and programmable non-von Neumann network utilized chaos to find the global minimum (the best solution) of any constrained optimization problem, and was able to solve the NP-hard traveling salesman problem 1000 times faster than the world's best digital supercomputer.

Biography: Suhas Kumar is a Postdoctoral Researcher and Principal Investigator at Hewlett Packard Labs, Palo Alto, CA. He earned a Ph.D. from Stanford University in 2014. He leads a group that investigates novel physical properties of materials and devices relevant to new forms of physics-driven and bio-inspired computing. His latest work includes a practical demonstration of the idea of using chaos to accelerate solutions to NP-hard problems. His research has been featured in dozens of scientific publications, conferences, patent applications, and popular media. His contributions were recently acknowledged with the Klein Scientific Development award.

Abstract: In this talk, I present our recent efforts in developing rigorous approaches to sparse sensor and actuator selection in large-scale linear dynamical systems. While sparse sensor and actuator selection is known to be NP-Hard, using tools from optimal experiment design and submodular optimization, we develop a framework for near- optimal sensor and actuator selection with provable approximation guarantees using greedy algorithms. We then extend these results to develop a robust variant of the approximations themes, where the optimization of sensor selection is performed in presence of an adversary who can cause a subset of sensors to fail. Next, using recent developments in graph sparsification and column selection literature, we show how to select a sparse subset of sensors or actuators while guaranteeing performance with respect to the fully sensed or actuated system (and not the optimal sparse one). As a corollary we show that by utilizing a time varying sense or actuator selection schedule, one can guarantee near-optimal sensing/control performance by selecting a dimension-independent (constant) number of sensors or actuators. Joint work with Vassilis Tzoumas (Penn), Milad Siami (MIT), and Alex Olshevsky (BU)

Biography: Ali Jadbabaie is the JR East Professor of Engineering and Associate Director of the Institute for Data, Systems and Society at MIT, where he is also on the faculty of the department of civil and environmental engineering and a principal investigator in the Laboratory for Information and Decision Systems (LIDS), and the director of the Sociotechnical Systems Research Center, one of MIT's 13 research laboratories. He received his Bachelors (with high honors) from Sharif University of Technology in Tehran, Iran, a Masters degree in electrical and computer engineering from the University of New Mexico, and his PhD in control and dynamical systems from the California Institute of Technology. He was a postdoctoral scholar at Yale University before joining the faculty at Penn in July 2002 where he was the Alfred Fitler Moore a Professor of Network Science. He was the inaugural editor-in-chief of IEEE Transactions on Network Science and Engineering, a new interdisciplinary journal sponsored by several IEEE societies. He is a recipient of a National Science Foundation Career Award, an Office of Naval Research Young Investigator Award, the O. Hugo Schuck Best Paper Award from the American Automatic Control Council, and the George S. Axelby Best Paper Award from the IEEE Control Systems Society. His students have been winners and finalists of student best paper awards at various ACC and CDC conferences. He is an IEEE fellow and a recipient of the 2016 Vannevar Bush Fellowship from the office of Secretary of Defense, and a member of the National Academies of Science, Engineering, and Medicine's Intelligence Science and Technology Expert Group (ISTEG). His current research interests are in distributed decision making and optimization, multi-agent coordination and control, network science, and network economics.